Updating per batch times based on batch_size=50 runs

llvm/projects/hpvm-tensor-rt/bin/time_jetson_profiles.py

@@ -30,8 +30,13 @@ ResNet50.batch_size = 50
 ResNet18 = Benchmark()
 ResNet18.binary_path = "resnet18_cifar10"
 #ResNet50.binary_time = 5.1 * 60  # 5.1 mins * 60 secs/min
-ResNet18.binary_time = 12.9  # 50 images * 100 batches
-ResNet18.batch_time = 12.9 / 50  # Time for batch with 50 images
+#ResNet18.binary_time = 12.9  # 50 images * 100 batches
+#ResNet18.batch_time = 12.9 / 50  # Time for batch with 50 images
+
+# Updated numbers based on batch_size = 50 -- NOTE: Underutilizes GPU - this can be better
+ResNet18.binary_time = 78  # 50 images * 100 batches
+ResNet18.batch_time = 78 / 100  # Time for batch with 50 images
+
 ResNet18.num_layers = 21
 ResNet18.data_size = 50 * 3 * 32 * 32 * 4   # *4 for Float32 Data
 ResNet18.num_classes = 10
@@ -39,6 +44,17 @@ ResNet18.batch_size = 50
 
 
 
+MobileNet = Benchmark()
+MobileNet.binary_path = "mobilenet_cifar10"
+MobileNet.binary_time = 103.0  # 50 images * 100 batches
+MobileNet.batch_time = 103.0 / 100  # Time for batch with 50 images
+MobileNet.num_layers = 15
+MobileNet.data_size = 50 * 3 * 32 * 32 * 4   # *4 for Float32 Data
+MobileNet.num_classes = 10
+MobileNet.batch_size = 50
+
+
+
 VGG16_ImageNet = Benchmark()
 VGG16_ImageNet.binary_path = "vgg16_imagenet"
 #VGG16_ImageNet.binary_time = 10.6 * 60  # 5.1 mins * 60 secs/min
@@ -52,8 +68,13 @@ VGG16_ImageNet.batch_size = 50
 
 VGG16_CIFAR10 = Benchmark()
 VGG16_CIFAR10.binary_path = "vgg16_cifar10"
-VGG16_CIFAR10.binary_time = 19.0  # 50 images * 100 batches
-VGG16_CIFAR10.batch_time = 19.0 /50
+#VGG16_CIFAR10.binary_time = 19.0  # 50 images * 100 batches
+#VGG16_CIFAR10.batch_time = 19.0 /50
+
+# Updated numbers based on batch_size = 50 -- NOTE: Underutilizes GPU - this can be better
+VGG16_CIFAR10.binary_time = 55.7  # 50 images * 100 batches
+VGG16_CIFAR10.batch_time = 55.7 / 100
+
 VGG16_CIFAR10.num_layers = 15
 VGG16_CIFAR10.data_size = 50 * 3 * 32 * 32 * 4
 VGG16_CIFAR10.num_classes = 10
@@ -61,9 +82,9 @@ VGG16_CIFAR10.batch_size = 50
 
 
 VGG16_CIFAR100 = Benchmark()
-VGG16_CIFAR100.binary_path = "vgg16_cifar10"
-VGG16_CIFAR100.binary_time = 19.0  # 50 images * 100 batches
-VGG16_CIFAR100.batch_time = 19.0 /50
+VGG16_CIFAR100.binary_path = "vgg16_cifar100"
+VGG16_CIFAR100.binary_time = 55.7  # 50 images * 100 batches
+VGG16_CIFAR100.batch_time = 55.7 / 100
 VGG16_CIFAR100.num_layers = 15
 VGG16_CIFAR100.data_size = 50 * 3 * 32 * 32 * 4
 VGG16_CIFAR100.num_classes = 100
@@ -73,8 +94,8 @@ VGG16_CIFAR100.batch_size = 50
 
 AlexNet_ImageNet = Benchmark()
 AlexNet_ImageNet.binary_path = "alexnet_imagenet"
-AlexNet_ImageNet.binary_time = 0.66 * 100  
-AlexNet_ImageNet.batch_time = 0.66
+AlexNet_ImageNet.binary_time = 0.7 * 100  
+AlexNet_ImageNet.batch_time = 0.7
 AlexNet_ImageNet.num_layers = 8
 AlexNet_ImageNet.data_size = 50 * 3 * 224 * 224 * 4
 AlexNet_ImageNet.num_classes = 1000
@@ -84,8 +105,8 @@ AlexNet_ImageNet.batch_size = 50
 
 AlexNet_CIFAR10 = Benchmark()
 AlexNet_CIFAR10.binary_path = "alexnet_cifar10"
-AlexNet_CIFAR10.binary_time = 13.52  
-AlexNet_CIFAR10.batch_time = 13.52 / 50 
+AlexNet_CIFAR10.binary_time = 23.52  
+AlexNet_CIFAR10.batch_time = 23.52 / 100 
 AlexNet_CIFAR10.num_layers = 6
 AlexNet_CIFAR10.data_size = 50 * 3 * 32 * 32 * 4
 AlexNet_CIFAR10.num_classes = 10
@@ -94,8 +115,8 @@ AlexNet_CIFAR10.batch_size = 50
 
 AlexNet2_CIFAR10 = Benchmark()
 AlexNet2_CIFAR10.binary_path = "alexnet2_cifar10"
-AlexNet2_CIFAR10.binary_time = 5.6  
-AlexNet2_CIFAR10.batch_time = 5.6 / 50 
+AlexNet2_CIFAR10.binary_time = 27.1  
+AlexNet2_CIFAR10.batch_time = 27.1 / 100 
 AlexNet2_CIFAR10.num_layers = 7
 AlexNet2_CIFAR10.data_size = 50 * 3 * 32 * 32 * 4
 AlexNet2_CIFAR10.num_classes = 10
@@ -105,8 +126,8 @@ AlexNet2_CIFAR10.batch_size = 50
 
 LeNet_CIFAR10 = Benchmark()
 LeNet_CIFAR10.binary_path = "lenet_keras"
-LeNet_CIFAR10.binary_time = 1.21  
-LeNet_CIFAR10.batch_time = 1.21 / 50 
+LeNet_CIFAR10.binary_time = 2.5  
+LeNet_CIFAR10.batch_time = 2.5 / 50 
 LeNet_CIFAR10.num_layers = 4
 LeNet_CIFAR10.data_size = 50 * 3 * 32 * 32 * 4
 LeNet_CIFAR10.num_classes = 10
@@ -208,6 +229,11 @@ if __name__ == "__main__":
     resnet18_time = getTimeOnEdge(ResNet18)
     print ("*** ResNet18 time (mins) = ", resnet18_time)
 
+
+    mobilenet_time = getTimeOnEdge(MobileNet)
+    print ("*** MobileNet time (mins) = ", mobilenet_time)
+
+    
     vgg16_img_time = getTimeOnEdge(VGG16_ImageNet)
     print ("*** VGG16-Imagenet time (mins) = ", vgg16_img_time)